What EasyScale Does for AI Search Visibility

A software buyer can ask for a recommendation without ever visiting your site. They might search Google for the best onboarding tool for a B2B SaaS company, or ask ChatGPT which product to buy. If the answer names three other companies, the missed opportunity may not appear in analytics at all.

That is the problem EasyScale is built around. It looks for the questions where buyers appear to be choosing between products, checks which companies are named in the answers, and creates content intended to improve your chances of being included. The focus is not traditional traffic reporting. It is finding where your product is absent from the answers that influence a purchase.

The problem is visibility before the click

Normal website analytics can show visits, conversions and referral sources. They cannot easily show a buyer who asked an AI assistant for advice, saw a competitor, and never reached your domain. EasyScale’s premise is that this missing visibility matters for software companies, especially when product selection begins with a recommendation rather than a branded search.

The service starts with your domain. According to its description, it works out what you sell and builds 20 questions that buyers ask when choosing a product. Those questions are then run each week through Google, ChatGPT, Gemini and Perplexity. EasyScale says it saves 240 answers from this process.

That monitoring gives the product a specific job. It is not simply asking whether your brand appears online. It is looking at buying questions and identifying cases where a competitor is named instead of you. For a SaaS company, that could make the output more useful than a broad list of keywords, because each question is tied to a product choice.

It turns a missing mention into an article

Once EasyScale finds a question where a competitor appears, it writes an article intended to answer that question properly. The article can be published to WordPress, Webflow, Ghost, or a company’s own stack through a webhook.

There is an approval step before anything ships. The developer says this takes about ten minutes a month. That matters because automatic publishing is a poor fit for many product teams. A draft that mentions the wrong audience, misunderstands a feature, or makes an unsupported comparison can create more work than it removes. EasyScale’s workflow leaves the final decision with the user, at least according to the supplied description.

The product’s claimed distinction is the connection between the content and the monitored answers. Each article is tied back to the specific AI answers and rankings that changed after publication. The following month’s plan is then based on those changes. In practical terms, the proposed workflow is: find a missing mention, publish a reviewed response, observe the answers again, and use the results to choose the next content.

That is a narrower promise than general-purpose SEO automation. It is also easier to understand. The system is aimed at recommendation questions, not every possible source of organic traffic.

Where the approach falls short

EasyScale does not give a company control over what Google or an AI assistant recommends. Monitoring and publishing content may improve a product’s chance of being considered, but the description does not promise inclusion in any answer. The buyer still has to trust the source, and the underlying search systems still decide what to show.

Its monitoring is also limited to the sources named in the description: Google, ChatGPT, Gemini and Perplexity. If your buyers rely on another search or AI service, that behaviour is outside the process described here. The same applies to questions that are not among the 20 EasyScale identifies. This is not a complete picture of every conversation about your category.

There is a further manual dependency. Although the product automates research and drafting, someone must review the articles before they are published. That is a sensible safeguard, but teams looking for unattended content production should not treat this as fully automatic publishing.

EasyScale runs on the web and through an API. It has a free plan with a paid upgrade, which the developer describes as free forever. The supported publishing routes are WordPress, Webflow, Ghost and a webhook to your own stack, so the fit depends partly on whether your site can use one of those paths.

Who should use EasyScale

EasyScale is aimed at SaaS, software, B2B SaaS and B2C SaaS companies that want to understand how their products appear in recommendation-led searches. It makes the most sense for a team that can identify its buying questions, review occasional drafts, and judge whether changes in AI answers are useful enough to guide the next month’s work.

It is not a good fit for a company seeking broad marketing analytics, guaranteed AI recommendations, or content that publishes without review. It is a focused monitoring and content workflow for a specific blind spot: the product mentions that never become a website visit.